Compact Data Association in Multiple Object Tracking: Pedestrian Tracking on Mobile Vehicle as Case Study

Piao, Songlin; Sutjaritvorakul, Tanittha; Berns, Karsten

doi:10.1016/j.ifacol.2016.07.728

Cited by 4 publications

(1 citation statement)

References 20 publications

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“…Zhang et al [12] only used a single camera but achieved an accuracy of over 90% through hierarchical detection, while Hane et al [13] obtained a powerful recognition effect by analyzing wheel speed and detecting multiple-frame images. Other examples are as follows: the integral channel algorithm proposed by Piotr Dollar et al, the lane line detection algorithm presented by Zhao et al [14], and the multiobjective trajectory tracking algorithm [15] developed by Piao et al…”

Section: Machine Vision (Video Camera)mentioning

confidence: 99%

Sensor-Based Environmental Perception Technology for Intelligent Vehicles

et al. 2021

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Environmental perception technology is the basis and premise of intelligent vehicle decision control of intelligent vehicles, a crucial link of intelligent vehicles to realize intelligence, and also the basic guarantee of its safety and intelligence. The accuracy and robustness of the perception algorithm will directly affect or even determine the realization of the upper function of intelligent vehicles. The wrong environmental perception will affect the control of the vehicle, thus causing safety risks. This paper discusses the intelligent vehicle perception technology and introduces the development status and control strategies of several important sensors such as machine vision, laser radar, and millimeter-wave radar. Target detection, target recognition, and multisensor fusion are analyzed in the optimized part of sensor results. The functions of the intelligent vehicle assistance system which has been applied to the ground at present are described, and the lane detection, adaptive cruise control (ACC), and autonomous emergency braking (AEB) are analyzed. Finally, the paper looks forward to the research direction of sense-based intelligent vehicle perception technology, which will play an important role in guiding the development of intelligent vehicles and accelerate the landing process of intelligent vehicles.

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Section: Machine Vision (Video Camera)mentioning

confidence: 99%